[ACT-R-users] Model of writing

[Paul J. Reber]

This might be just slightly off the general writing/typing topic, but 
has anybody played around with an ACT-R model of something like playing 
Guitar Hero?  We're using a task something like this in the lab (without 
music) to look at sequence learning and thinking about the general 
process of skill acquisition (in perceptual-motor tasks).

The relation to typing would be why you might be quicker to type 
familiar words/phrases due to prior practice frequently typing them.

Paul
-- 
Paul J. Reber, Ph.D.
Department of Psychology
Northwestern University

Dan Bothell wrote:
> 
> To test the question about 1 fingered, 2 fingered, and 10 fingered
> typists in ACT-R I created some test models (if you could even call
> them that because they're mostly just Lisp code) which just push motor
> requests through to type out sentences repeatedly for 60 seconds to
> get a words/minute score (where a word is every 5 keypresses).  Those
> models were then tested across the three possibilities for pipelining
> of motor actions: "state free", "processor free", and "preparation free".
> 
> There were 5 total models:
> 
> One-finger is a good "hunt and peck" typist using only one finger.
> 
> Two-fingers is a good "hunt and peck" typist using both index fingers
>  keeping each hand on its own side of the keyboard.
> 
> Ten-fingers is a model which uses the default press-key action to
>  touch-type using all fingers.
> 
> One-finger-savant is a perfect touch-typist using only one index finger
>  i.e. it can move that finger from any key to hit any other key
>  perfectly as a single action, without looking.
> 
> Two-finger-savant is a perfect touch-typist using both index fingers
>  where each finger stays on its own side of the keyboard.
> 
> Here's the average WPM I got based on 3 simple sentences which
> each have all the letters of the alphabet at least once:
> 
>                   state free   processor free    preparation free
> one-finger            13.0           19.1                X
> two-fingers           13.8           20.7                X
> ten-fingers           25.3           40.9              47.5
> one-finger-savant     30.5           44.6                X
> two-finger-savant     28.3           44.1                X
> 
> The code is attached if anyone wants to look at the individual
> sentence results (the function run-all-tests will run the models
> through all the conditions), but I wouldn't recommend it as a
> guide for how to write an ACT-R model.  :)
> 
> Here are the things which I found interesting.
> 
> - The fastest overall was the ten fingered model in the "preparation
> free" case at 47.5 wpm, which is faster than I expected.
> 
> - Testing "preparation free" actually lead to typing errors for the one-
> and two-fingered models since it was modifying the features before the
> last action had begun (the finger was trying to do two things at once).
> So, those models are skipped for that condition.
> 
> - In the other cases the ten fingered model beats the "hunt and peck"
> models as expected, but the "savant" models were faster than the
> ten fingered one.  So the savings in preparation time is better than
> the cost of the extra movement relative to the press-key actions
> with the default motor module parameters.  However, from a plausibility
> standpoint what those savant models do seems pretty super human to me.
> 
> 
> Dan
> 
> 
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